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import os
import glob
import pickle
import numpy as np
import h5py
from .base_dumper import BaseDumper
import sys
ROOT_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../"))
sys.path.insert(0, ROOT_DIR)
import utils
class yfcc(BaseDumper):
def get_seqs(self):
data_dir=os.path.join(self.config['rawdata_dir'],'yfcc100m')
for seq in self.config['data_seq']:
for split in self.config['data_split']:
split_dir=os.path.join(data_dir,seq,split)
dump_dir=os.path.join(self.config['feature_dump_dir'],seq,split)
cur_img_seq=glob.glob(os.path.join(split_dir,'images','*.jpg'))
cur_dump_seq=[os.path.join(dump_dir,path.split('/')[-1])+'_'+self.config['extractor']['name']+'_'+str(self.config['extractor']['num_kpt'])\
+'.hdf5' for path in cur_img_seq]
self.img_seq+=cur_img_seq
self.dump_seq+=cur_dump_seq
def format_dump_folder(self):
if not os.path.exists(self.config['feature_dump_dir']):
os.mkdir(self.config['feature_dump_dir'])
for seq in self.config['data_seq']:
seq_dir=os.path.join(self.config['feature_dump_dir'],seq)
if not os.path.exists(seq_dir):
os.mkdir(seq_dir)
for split in self.config['data_split']:
split_dir=os.path.join(seq_dir,split)
if not os.path.exists(split_dir):
os.mkdir(split_dir)
def format_dump_data(self):
print('Formatting data...')
pair_path=os.path.join(self.config['rawdata_dir'],'pairs')
self.data={'K1':[],'K2':[],'R':[],'T':[],'e':[],'f':[],'fea_path1':[],'fea_path2':[],'img_path1':[],'img_path2':[]}
for seq in self.config['data_seq']:
pair_name=os.path.join(pair_path,seq+'-te-1000-pairs.pkl')
with open(pair_name, 'rb') as f:
pairs=pickle.load(f)
#generate id list
seq_dir=os.path.join(self.config['rawdata_dir'],'yfcc100m',seq,'test')
name_list=np.loadtxt(os.path.join(seq_dir,'images.txt'),dtype=str)
cam_name_list=np.loadtxt(os.path.join(seq_dir,'calibration.txt'),dtype=str)
for cur_pair in pairs:
index1,index2=cur_pair[0],cur_pair[1]
cam1,cam2=h5py.File(os.path.join(seq_dir,cam_name_list[index1]),'r'),h5py.File(os.path.join(seq_dir,cam_name_list[index2]),'r')
K1,K2=cam1['K'][()],cam2['K'][()]
[w1,h1],[w2,h2]=cam1['imsize'][()][0],cam2['imsize'][()][0]
cx1,cy1,cx2,cy2 = (w1 - 1.0) * 0.5,(h1 - 1.0) * 0.5, (w2 - 1.0) * 0.5,(h2 - 1.0) * 0.5
K1[0,2],K1[1,2],K2[0,2],K2[1,2]=cx1,cy1,cx2,cy2
R1,R2,t1,t2=cam1['R'][()],cam2['R'][()],cam1['T'][()].reshape([3,1]),cam2['T'][()].reshape([3,1])
dR = np.dot(R2, R1.T)
dt = t2 - np.dot(dR, t1)
dt /= np.sqrt(np.sum(dt**2))
e_gt_unnorm = np.reshape(np.matmul(
np.reshape(utils.evaluation_utils.np_skew_symmetric(dt.astype('float64').reshape(1, 3)), (3, 3)),
np.reshape(dR.astype('float64'), (3, 3))), (3, 3))
e_gt = e_gt_unnorm / np.linalg.norm(e_gt_unnorm)
f_gt_unnorm=np.linalg.inv(K2.T)@e_gt@np.linalg.inv(K1)
f_gt = f_gt_unnorm / np.linalg.norm(f_gt_unnorm)
self.data['K1'].append(K1),self.data['K2'].append(K2)
self.data['R'].append(dR),self.data['T'].append(dt)
self.data['e'].append(e_gt),self.data['f'].append(f_gt)
img_path1,img_path2=os.path.join('yfcc100m',seq,'test',name_list[index1]),os.path.join('yfcc100m',seq,'test',name_list[index2])
dump_seq_dir=os.path.join(self.config['feature_dump_dir'],seq,'test')
fea_path1,fea_path2=os.path.join(dump_seq_dir,name_list[index1].split('/')[-1]+'_'+self.config['extractor']['name']
+'_'+str(self.config['extractor']['num_kpt'])+'.hdf5'),\
os.path.join(dump_seq_dir,name_list[index2].split('/')[-1]+'_'+self.config['extractor']['name']
+'_'+str(self.config['extractor']['num_kpt'])+'.hdf5')
self.data['img_path1'].append(img_path1),self.data['img_path2'].append(img_path2)
self.data['fea_path1'].append(fea_path1),self.data['fea_path2'].append(fea_path2)
self.form_standard_dataset()
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